The document discusses the Entity-Relationship (ER) model for database design. It describes the ER model as having three phases: conceptual, logical, and physical design. The conceptual design produces an initial model of the application domain using the ER model. This model is then transformed into the logical relational model supported by the database management system. Physical design then optimizes performance. The document outlines the basic constructs of the ER model including entities, attributes, relationships, and how they are depicted in ER diagrams.
This document summarizes three papers on keyword search over structured databases using an interpretative approach. The first paper discusses building an efficient index table to map keywords to row and column identifiers in the database. The second paper presents a general algorithm with two steps - a publication step to pre-compute indexing, and a search step to lookup keywords and generate SQL queries. The third paper introduces the concept of intrinsic and contextual weights to model the dependency between query keywords and generate a ranked list of query interpretations.
This presentation contains the concepts related to database design using ER Diagram. The content is adapted from the contents of the authors of the book mentioned in the reference.
Islamic University Previous Year Question Solution 2019 (ADBMS)Rakibul Hasan Pranto
Database administrators (DBAs) manage databases and are responsible for tasks like creating the database schema, defining storage structures and access methods, modifying the schema or physical organization when needed, granting authorization for data access, and specifying integrity constraints. Other database roles include application programmers, sophisticated users, specialized users, standalone users, native users, and system analysts who are responsible for database design, structure, and properties.
The document presents a graphical approach called Graphical Notations-Data Type Documentation (GN-DTD) for normalizing XML documents. GN-DTD allows capturing the syntax and semantics of XML documents in a simple but precise way using various notations. It can visualize important XML features like elements, attributes, relationships, hierarchy, cardinality, sequence and disjunction clearly at the schema level. The paper then demonstrates how a sample DTD is transformed into a GN-DTD graph to represent the structure and constraints of an XML document and avoid potential data redundancies and update anomalies.
Object relationship mapping and hibernateJoe Jacob
ORM stands for Object Relational Mapping and is a technique for mapping objects in an object-oriented programming language to tables in a relational database. The document discusses the various mismatches that exist between object-oriented programming and relational databases, and how ORM frameworks like Hibernate address these mismatches through object relational mapping. It also provides an overview of Hibernate - a popular Java ORM framework, and demonstrates how to configure Hibernate and perform basic CRUD operations using both XML configuration and Java annotations.
This document discusses database design using Entity Relationship Diagrams (ERDs). It covers how to draw ERDs using Chen's Model and Crow's Foot notations and define the basic elements of ERDs. Conversion rules are presented to convert ERDs into relational tables for one-to-one, one-to-many, and many-to-many relationships. An example is given to demonstrate drawing an ERD for a company database and converting it into relational tables.
The document describes how to convert an entity-relationship (ER) model diagram into a relational database model. It explains that each entity set becomes a table, with columns for attributes and a primary key. Relationship sets may become tables, with columns for participating entity primary keys. Weak entity sets include a discriminator and strong entity primary key. Class hierarchies use a primary key from the super class for subclasses.
(1) The document describes different approaches to translating an entity-relationship (ER) schema into a relational schema, including suppressing generalizations, keeping the superentity, and keeping subentities.
(2) It provides examples and evaluations of each approach, noting tradeoffs like optional attributes, redundant data, and complex queries.
(3) Rules are presented for mapping ER schema components like entities, relationships, and attributes into relational tables, including using foreign keys to represent one-to-one and one-to-many relationships.
This document summarizes three papers on keyword search over structured databases using an interpretative approach. The first paper discusses building an efficient index table to map keywords to row and column identifiers in the database. The second paper presents a general algorithm with two steps - a publication step to pre-compute indexing, and a search step to lookup keywords and generate SQL queries. The third paper introduces the concept of intrinsic and contextual weights to model the dependency between query keywords and generate a ranked list of query interpretations.
This presentation contains the concepts related to database design using ER Diagram. The content is adapted from the contents of the authors of the book mentioned in the reference.
Islamic University Previous Year Question Solution 2019 (ADBMS)Rakibul Hasan Pranto
Database administrators (DBAs) manage databases and are responsible for tasks like creating the database schema, defining storage structures and access methods, modifying the schema or physical organization when needed, granting authorization for data access, and specifying integrity constraints. Other database roles include application programmers, sophisticated users, specialized users, standalone users, native users, and system analysts who are responsible for database design, structure, and properties.
The document presents a graphical approach called Graphical Notations-Data Type Documentation (GN-DTD) for normalizing XML documents. GN-DTD allows capturing the syntax and semantics of XML documents in a simple but precise way using various notations. It can visualize important XML features like elements, attributes, relationships, hierarchy, cardinality, sequence and disjunction clearly at the schema level. The paper then demonstrates how a sample DTD is transformed into a GN-DTD graph to represent the structure and constraints of an XML document and avoid potential data redundancies and update anomalies.
Object relationship mapping and hibernateJoe Jacob
ORM stands for Object Relational Mapping and is a technique for mapping objects in an object-oriented programming language to tables in a relational database. The document discusses the various mismatches that exist between object-oriented programming and relational databases, and how ORM frameworks like Hibernate address these mismatches through object relational mapping. It also provides an overview of Hibernate - a popular Java ORM framework, and demonstrates how to configure Hibernate and perform basic CRUD operations using both XML configuration and Java annotations.
This document discusses database design using Entity Relationship Diagrams (ERDs). It covers how to draw ERDs using Chen's Model and Crow's Foot notations and define the basic elements of ERDs. Conversion rules are presented to convert ERDs into relational tables for one-to-one, one-to-many, and many-to-many relationships. An example is given to demonstrate drawing an ERD for a company database and converting it into relational tables.
The document describes how to convert an entity-relationship (ER) model diagram into a relational database model. It explains that each entity set becomes a table, with columns for attributes and a primary key. Relationship sets may become tables, with columns for participating entity primary keys. Weak entity sets include a discriminator and strong entity primary key. Class hierarchies use a primary key from the super class for subclasses.
(1) The document describes different approaches to translating an entity-relationship (ER) schema into a relational schema, including suppressing generalizations, keeping the superentity, and keeping subentities.
(2) It provides examples and evaluations of each approach, noting tradeoffs like optional attributes, redundant data, and complex queries.
(3) Rules are presented for mapping ER schema components like entities, relationships, and attributes into relational tables, including using foreign keys to represent one-to-one and one-to-many relationships.
1. The Covers relationship is ternary, involving Employees, Policies, and Dependents relations, while Purchaser and Beneficiary are binary relationships.
2. Ternary relationships impose stronger constraints - a policy must be linked to a specific employee and dependent.
3. The second diagram models the relationships more accurately by separating the purchaser, beneficiary, and policy linkages. This removes ambiguities of the ternary relationship.
My Autodesk University 2009 presentation. It was about aligning the Data Model to the business and the capabilities of AutoCAD Map for utility modeling
An Object Oriented DBMS stores data as objects that use object-oriented concepts like classes, inheritance, and encapsulation. Objects have attributes that can be simple like integers or complex like collections. Classes group similar objects and subclasses inherit attributes and behaviors from superclasses. Objects communicate through messages that invoke methods. The DBMS maps classes and objects to tables and tuples in a relational database, which loses some semantic information about class hierarchies.
The document is a lab manual for the subject GUI and Database Management in the Department of Information Technology at K. J. Somaiya Institute of Engineering & Information Technology. It outlines 10 experiments involving entity relationship modeling, implementing a database using SQL Server, modifying the database schema, implementing simple and advanced SQL queries, joins, views, designing a graphical user interface using VB 6.0, connecting the GUI to a database, and developing a working module. The experiments aim to teach students how to design databases, implement them, query and manipulate data, and connect a user interface.
This document discusses the process of database design, including conceptual modeling using entity-relationship (ER) diagrams. It begins by outlining the initial requirements gathering and conceptual modeling phases. Next, it describes logical and physical design, which involve mapping the conceptual model to relational schemas and deciding on physical storage structures. The bulk of the document then focuses on concepts in ER modeling, including entities, attributes, relationships, relationship types, weak entities, and how to represent these graphically in an ER diagram. It provides examples to illustrate key ER modeling concepts and design issues.
The document describes a PowerPoint presentation on database management systems. Specifically, it outlines the topics to be covered in each lecture and provides the corresponding slide numbers. The topics include the history of database systems from the 1950s to present day, database design using entity-relationship diagrams, relationships and sets, additional features of the ER model like keys and constraints, conceptual design using the ER model, and large enterprises. It also includes sample slides on the history of databases and modeling entities, attributes, and relationships.
This document provides an overview of SQL, including its objectives, history, data definition and manipulation languages, and basic concepts. It discusses SQL's purpose in creating database structures and performing tasks like inserts, updates, deletes, and queries. The document also covers SQL datatypes, keywords for queries, updates, and deletes, and both advantages and disadvantages of SQL.
The document discusses elements of database design including:
1) Relations and functions, defining relations as relationships between sets of information represented by ordered pairs, and functions as relations where each domain has only one range.
2) Trees and tree structures, defining trees as subsets of graphs with vertices connected by edges, and distinguishing between binary and n-ary trees.
3) Ways to traverse trees including breadth-first search, which moves level-by-level, and depth-first search, which prioritizes reaching the greatest depth of each path before backtracking.
Chapter-2 Database System Concepts and ArchitectureKunal Anand
This document provides an overview of database management systems concepts and architecture. It discusses different data models including hierarchical, network, relational, entity-relationship, object-oriented, and object-relational models. It also describes the 3-schema architecture with external, conceptual, and internal schemas and explains components of a DBMS including users, storage and query managers. Finally, it covers database languages like DDL, DML, and interfaces like menu-based, form-based and graphical user interfaces.
The document discusses key concepts of the relational database model including how tables represent data through relations, attributes, tuples, and domains. It defines primary keys, foreign keys, entity integrity and referential integrity. Views are described as virtual relations defined by queries on base relations that dynamically reflect changes to the underlying data. The purpose of views is to provide security, customization of data access, and simplification of complex queries. There are restrictions on updating data through views.
This document discusses database schema integration and transaction design. It describes taking individual schemas designed by different groups and merging them into a single global schema by identifying correspondences and resolving conflicts. Conflicts can include naming, data type, domain, and constraint inconsistencies. Strategies for the merging process include binary ladder integration, n-ary integration, and binary balanced integration. The document also discusses designing the functional characteristics of known database transactions during the design phase, categorizing them as retrieval, update, or mixed transactions.
This slideshow outlines LSC Digital's process of building, maintaining, and executing a customer database across multiple channels, including e-mail, PPC and Internet display ads, and traditional direct mail.
A Practitioner's Guide to Successfully Migrate from Oracle to Sybase ASE Part 2Dobler Consulting
This document provides an overview of migrating from Oracle to Sybase ASE. It discusses comparing the key differences between Oracle and Sybase ASE, including processes, case sensitivity, storage architecture, transactions, parallel execution and more. It also covers performing a portability check to identify migration issues and develop workarounds, such as how to handle Oracle triggers, synonyms, sequences, materialized views and different table types in Sybase ASE. The document is intended to help successfully migrate applications with minimal code rewrites.
Database design involves three phases: conceptual design, logical design, and physical design. The conceptual design focuses on data requirements and results. The logical design describes the structure of the database. The physical design describes the implementation including programs, tables, and catalogs. Conceptual models represent data at a high level of abstraction while logical models can be processed by computers. Entity-relationship diagrams are commonly used for conceptual modeling and show entities, relationships, attributes, and other aspects.
The document describes the steel making process and its entity relationship diagram. The major steps in steel making are: coke oven, blast furnace, LD converter, secondary refining, and casting. Raw materials like iron ore, coal, and limestone are transformed through these steps into finished steel products like slabs, bars, and coils. The entity relationship diagram shows the relationships between vendors, raw materials, finished steel, products, and customers in the steel making process.
The document provides tips and guidelines for optimizing performance of SAP Sybase ASE, covering planning, configuration, running/monitoring, and troubleshooting. It discusses topics like hardware sizing, operating system configuration, database configuration parameters, query optimization goals, monitoring tools like MDA, and troubleshooting techniques using set options and MDA tables. The goal is to provide novices and experienced DBAs with information to enhance ASE performance.
In this presentation, attendees will learn how to determine the best approach for tuning SQL statements and other issues by identifying specific causes of slow performance. Real-life case studies will be used to demonstrate:
1.How to use Response Time Analysis (RTA) to quickly identify the biggest problems in a database
2.How to utilize the MDA tables to understand what resources are being used or waited on
3.Tips and techniques on examining and further fine-tuning the execution plan
The document discusses database design process which can be broken down into 5 phases - planning, analysis, design, implementation and maintenance. It describes the conceptual, logical and physical data models. The conceptual model involves entities, attributes and relationships. The logical model maps the conceptual model to tables, fields, primary and foreign keys. The physical model deals with data storage and access. The document also covers entity relationship diagrams, normalization forms and tips for effective ER diagrams.
The document discusses database design and the design process. It explains that database design involves determining the relationships between data elements, structuring them logically, and specifying attributes. The design process includes determining the database purpose, finding and organizing information, dividing it into tables, specifying columns and primary keys, and setting up relationships. It also recommends creating child tables to store multiple pieces of information rather than adding many fields to the core table. This improves the database structure and makes it more extensible.
Database Modeling Using Entity.. Weak And Strong Entity Typesaakanksha s
Data modeling is a technique for organizing data in a system by applying formal modeling methods. It involves creating conceptual, logical, and physical data models. Key elements of data modeling include entities, attributes, relationships, domains, keys, and cardinality. Weak entities differ from strong entities in that weak entities do not have attributes to form a primary key and instead inherit their primary key from the strong entity they are dependent on through an identifying relationship.
1. The Covers relationship is ternary, involving Employees, Policies, and Dependents relations, while Purchaser and Beneficiary are binary relationships.
2. Ternary relationships impose stronger constraints - a policy must be linked to a specific employee and dependent.
3. The second diagram models the relationships more accurately by separating the purchaser, beneficiary, and policy linkages. This removes ambiguities of the ternary relationship.
My Autodesk University 2009 presentation. It was about aligning the Data Model to the business and the capabilities of AutoCAD Map for utility modeling
An Object Oriented DBMS stores data as objects that use object-oriented concepts like classes, inheritance, and encapsulation. Objects have attributes that can be simple like integers or complex like collections. Classes group similar objects and subclasses inherit attributes and behaviors from superclasses. Objects communicate through messages that invoke methods. The DBMS maps classes and objects to tables and tuples in a relational database, which loses some semantic information about class hierarchies.
The document is a lab manual for the subject GUI and Database Management in the Department of Information Technology at K. J. Somaiya Institute of Engineering & Information Technology. It outlines 10 experiments involving entity relationship modeling, implementing a database using SQL Server, modifying the database schema, implementing simple and advanced SQL queries, joins, views, designing a graphical user interface using VB 6.0, connecting the GUI to a database, and developing a working module. The experiments aim to teach students how to design databases, implement them, query and manipulate data, and connect a user interface.
This document discusses the process of database design, including conceptual modeling using entity-relationship (ER) diagrams. It begins by outlining the initial requirements gathering and conceptual modeling phases. Next, it describes logical and physical design, which involve mapping the conceptual model to relational schemas and deciding on physical storage structures. The bulk of the document then focuses on concepts in ER modeling, including entities, attributes, relationships, relationship types, weak entities, and how to represent these graphically in an ER diagram. It provides examples to illustrate key ER modeling concepts and design issues.
The document describes a PowerPoint presentation on database management systems. Specifically, it outlines the topics to be covered in each lecture and provides the corresponding slide numbers. The topics include the history of database systems from the 1950s to present day, database design using entity-relationship diagrams, relationships and sets, additional features of the ER model like keys and constraints, conceptual design using the ER model, and large enterprises. It also includes sample slides on the history of databases and modeling entities, attributes, and relationships.
This document provides an overview of SQL, including its objectives, history, data definition and manipulation languages, and basic concepts. It discusses SQL's purpose in creating database structures and performing tasks like inserts, updates, deletes, and queries. The document also covers SQL datatypes, keywords for queries, updates, and deletes, and both advantages and disadvantages of SQL.
The document discusses elements of database design including:
1) Relations and functions, defining relations as relationships between sets of information represented by ordered pairs, and functions as relations where each domain has only one range.
2) Trees and tree structures, defining trees as subsets of graphs with vertices connected by edges, and distinguishing between binary and n-ary trees.
3) Ways to traverse trees including breadth-first search, which moves level-by-level, and depth-first search, which prioritizes reaching the greatest depth of each path before backtracking.
Chapter-2 Database System Concepts and ArchitectureKunal Anand
This document provides an overview of database management systems concepts and architecture. It discusses different data models including hierarchical, network, relational, entity-relationship, object-oriented, and object-relational models. It also describes the 3-schema architecture with external, conceptual, and internal schemas and explains components of a DBMS including users, storage and query managers. Finally, it covers database languages like DDL, DML, and interfaces like menu-based, form-based and graphical user interfaces.
The document discusses key concepts of the relational database model including how tables represent data through relations, attributes, tuples, and domains. It defines primary keys, foreign keys, entity integrity and referential integrity. Views are described as virtual relations defined by queries on base relations that dynamically reflect changes to the underlying data. The purpose of views is to provide security, customization of data access, and simplification of complex queries. There are restrictions on updating data through views.
This document discusses database schema integration and transaction design. It describes taking individual schemas designed by different groups and merging them into a single global schema by identifying correspondences and resolving conflicts. Conflicts can include naming, data type, domain, and constraint inconsistencies. Strategies for the merging process include binary ladder integration, n-ary integration, and binary balanced integration. The document also discusses designing the functional characteristics of known database transactions during the design phase, categorizing them as retrieval, update, or mixed transactions.
This slideshow outlines LSC Digital's process of building, maintaining, and executing a customer database across multiple channels, including e-mail, PPC and Internet display ads, and traditional direct mail.
A Practitioner's Guide to Successfully Migrate from Oracle to Sybase ASE Part 2Dobler Consulting
This document provides an overview of migrating from Oracle to Sybase ASE. It discusses comparing the key differences between Oracle and Sybase ASE, including processes, case sensitivity, storage architecture, transactions, parallel execution and more. It also covers performing a portability check to identify migration issues and develop workarounds, such as how to handle Oracle triggers, synonyms, sequences, materialized views and different table types in Sybase ASE. The document is intended to help successfully migrate applications with minimal code rewrites.
Database design involves three phases: conceptual design, logical design, and physical design. The conceptual design focuses on data requirements and results. The logical design describes the structure of the database. The physical design describes the implementation including programs, tables, and catalogs. Conceptual models represent data at a high level of abstraction while logical models can be processed by computers. Entity-relationship diagrams are commonly used for conceptual modeling and show entities, relationships, attributes, and other aspects.
The document describes the steel making process and its entity relationship diagram. The major steps in steel making are: coke oven, blast furnace, LD converter, secondary refining, and casting. Raw materials like iron ore, coal, and limestone are transformed through these steps into finished steel products like slabs, bars, and coils. The entity relationship diagram shows the relationships between vendors, raw materials, finished steel, products, and customers in the steel making process.
The document provides tips and guidelines for optimizing performance of SAP Sybase ASE, covering planning, configuration, running/monitoring, and troubleshooting. It discusses topics like hardware sizing, operating system configuration, database configuration parameters, query optimization goals, monitoring tools like MDA, and troubleshooting techniques using set options and MDA tables. The goal is to provide novices and experienced DBAs with information to enhance ASE performance.
In this presentation, attendees will learn how to determine the best approach for tuning SQL statements and other issues by identifying specific causes of slow performance. Real-life case studies will be used to demonstrate:
1.How to use Response Time Analysis (RTA) to quickly identify the biggest problems in a database
2.How to utilize the MDA tables to understand what resources are being used or waited on
3.Tips and techniques on examining and further fine-tuning the execution plan
The document discusses database design process which can be broken down into 5 phases - planning, analysis, design, implementation and maintenance. It describes the conceptual, logical and physical data models. The conceptual model involves entities, attributes and relationships. The logical model maps the conceptual model to tables, fields, primary and foreign keys. The physical model deals with data storage and access. The document also covers entity relationship diagrams, normalization forms and tips for effective ER diagrams.
The document discusses database design and the design process. It explains that database design involves determining the relationships between data elements, structuring them logically, and specifying attributes. The design process includes determining the database purpose, finding and organizing information, dividing it into tables, specifying columns and primary keys, and setting up relationships. It also recommends creating child tables to store multiple pieces of information rather than adding many fields to the core table. This improves the database structure and makes it more extensible.
Database Modeling Using Entity.. Weak And Strong Entity Typesaakanksha s
Data modeling is a technique for organizing data in a system by applying formal modeling methods. It involves creating conceptual, logical, and physical data models. Key elements of data modeling include entities, attributes, relationships, domains, keys, and cardinality. Weak entities differ from strong entities in that weak entities do not have attributes to form a primary key and instead inherit their primary key from the strong entity they are dependent on through an identifying relationship.
The document discusses the MySQL database design process. It covers defining keys to uniquely identify records, the different types of table relationships including one-to-one, one-to-many, and many-to-many, and the process of normalization to minimize duplication and inconsistencies. The three main levels of normalization discussed are first, second, and third normal forms, each with their own rules. Following proper database design, normalization, and defining relationships between tables is important for ensuring an efficient, flexible, and maintainable database structure.
Michael Joseph is giving a presentation on database normalization. He begins by explaining the importance of properly structuring data across database tables and the problems that can arise from poor database design, such as redundancy, inaccuracy, and consistency issues. He then describes database normalization as a process that organizes data to minimize redundancy by decomposing relations and isolating data in separate, well-defined tables connected through relationships. Different levels of normalization are discussed, with third normal form being sufficient for most applications. Examples are provided to illustrate how normalization progresses from first to third normal form. Potential issues with highly normalized databases are also outlined.
The document discusses the process of designing a database management system (DBMS). It describes the six phases of the database lifecycle: initial study, design, implementation, testing and evaluation, operation, and maintenance and evaluation. The design phase is the most critical, as it ensures the final system meets user requirements through conceptual, logical, and physical database design. Successful DBMS design requires balancing the needs of users, infrastructure, and management.
Database Normalization
The term Normalization is a process by which we can efficiently organize the data in a database. It associates relationship between individual tables according to policy designed both to care for the data and to create the database more flexible by eliminating redundancy and inconsistent dependency.
In other words, Database normalization is a process by which a presented database is tailored to bring its component tables into compliance with a sequence of progressive standard forms. It is an organized way of ensuring that a database construction is appropriate for general purpose querying and also includes the functions of insertion, deletion and updating.
Edgar Frank Codd was the person who introduced the process of database normalization firstly in his paper called A Relational Model of Data for Large Shared Data Banks. The two main objective of database normalization is eliminating redundant data and ensuring data dependencies make sense and make sure that every non-key column in every table is directly reliant on the key and the whole key.
Redundant data or unnecessary data will take more and more space in the database and later, creates the maintenance problem in the database. If data that exists in more than one place must be changed because it wastes disk space and the data must be changed in exactly the same way in all locations of the table.
Normalization is a technique for designing relational database tables to minimize duplication of data and ensure data integrity. It involves organizing data into tables and establishing relationships between tables based on their attributes. There are several normal forms like 1NF, 2NF and 3NF that provide rules for table design to reduce anomalies and inconsistencies. Functional dependencies define relationships between attributes in a table, and normalization aims to remove non-key attributes that are functionally dependent on other attributes.
The document discusses normalization in database design. Normalization is the process of organizing data to avoid redundancy and dependency. It involves splitting tables and restructuring relationships between tables. The document outlines various normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF and provides examples to illustrate how to normalize tables to conform to each form.
This document provides an overview of key database concepts, including:
- Types of databases and database management systems (DBMS) functions
- Data models like relational, hierarchical, and object-oriented
- The three-schema architecture with conceptual, internal, and external schemas
- Languages used to define and manipulate database structures and data
- Centralized and client-server database system architectures
This document provides an introduction and overview of databases and the basic operations used to manage data in a database using Microsoft Access 2007. It defines what a database is, how data is organized in tables with rows and columns, and when it is appropriate to use a database. It also outlines and provides examples of the basic CRUD (create, read, update, delete) operations used in structured query language (SQL) to manipulate data, including inserting, selecting, updating, and deleting records from database tables.
The document discusses database design and relational database management systems. It covers key concepts like normalization, primary keys, foreign keys, and relationships between tables. Normalization is the process of organizing data to eliminate redundancy and ensure data is stored correctly. There are five normal forms with third normal form being sufficient for most applications. Tables are related through primary and foreign keys and different types of relationships can exist between tables like one-to-one, one-to-many, and many-to-many.
The document discusses key concepts in relational data models including entities, attributes, relationships, and constraints. It provides examples of each concept and explains how they are the basic building blocks used to structure data in a relational database. Specific types of entities, attributes, relationships and their properties are defined, such as one-to-one, one-to-many, and many-to-many relationships. Overall, the document serves as an introduction to fundamental concepts in relational data modeling.
This document provides an overview of a database management systems course. The course objectives are to understand the purpose and concepts of DBMS, apply database design and languages to manage data, learn about normalization, SQL implementation, transaction control, recovery strategies, storage, and indexing. The outcomes are knowledge of various data models, database design process, transaction management, users and administration. Key topics covered include the relational and entity-relationship data models, database design, transactions, and database users and administration.
The document discusses various strategies for mapping object-oriented classes and relationships to relational databases. It describes mapping class attributes to database columns, implementing inheritance through single-table or multiple-table approaches, and mapping relationships like associations through foreign keys or associative tables. The strategies each have advantages and disadvantages related to ease of implementation, data access speed, coupling between classes, and support for polymorphism. There is no single best approach, and the optimal strategy depends on the specific application.
Natural Language Processing in R (rNLP)fridolin.wild
The introductory slides of a workshop given to the doctoral school at the Institute of Business Informatics of the Goethe University Frankfurt. The tutorials are available on http://crunch.kmi.open.ac.uk/w/index.php/Tutorials
Overview of Object-Oriented Concepts Characteristics by vikas jagtapVikas Jagtap
Object-oriented data base systems are proposed as alternative to relational systems and are aimed at application domains where complex objects play a central role.
The approach is heavily influenced by object-oriented programming languages and can be understood as an attempt to add DBMS functionality to a programming language environment
Object-Oriented Systems Analysis and Design Using UML.pptxXanGwaps
This document discusses object-oriented systems analysis and design using the Unified Modeling Language (UML). It defines object-oriented analysis and design, and explains that UML uses various diagrams to visualize the construction of object-oriented systems. The main components of UML include things, relationships, and diagrams. Key object-oriented concepts like objects, classes, attributes, and methods are also described. Finally, different types of UML diagrams like class, component, deployment, use case and activity diagrams are introduced along with examples.
The document discusses different data models used in database management systems including hierarchical, network, entity-relationship, and relational models.
The hierarchical model organizes data in a tree structure with one-to-many relationships. The network model extends the hierarchical model by allowing data to have more than one parent node.
The entity-relationship model views data as entities and relationships between entities. It provides a high-level conceptual view of data through entity-relationship diagrams. The relational model organizes data into tables and defines relationships through common fields. It is the most widely used data model today.
This document compares relational database management systems (RDBMS), object-oriented database management systems (OODBMS), and object-relational database management systems (ORDBMS).
It first discusses the differences between RDBMS and OODBMS in terms of data modeling and objectives. RDBMS model only data state while OODBMS model both state and behavior. It also compares their main objectives, with OODBMS focusing on encapsulation and independence and RDBMS on data independence from applications.
It then compares RDBMS and ORDBMS, noting that an ORDBMS is a RDBMS with SQL3 extensions like user-defined types and routines. A RDBMS is simpler and
The document discusses different types of data models including conceptual, physical, and implementation models. It describes key aspects of data models such as their structure, constraints, and operations. Specific models covered include the entity-relationship model, network model, object-oriented model, and relational model. Key components of the entity-relationship model like entities, attributes, relationships, and ER diagrams are defined. The network and object-oriented models are also briefly explained.
The document discusses enhanced entity-relationship (EER) modeling concepts, including subclasses and superclasses, specialization and generalization, categories, and attribute inheritance. It provides examples of each concept and constraints on specialization and generalization. Key points include:
- Subclasses represent subgroups of a superclass and inherit attributes and relationships.
- Specialization defines subclasses based on distinguishing characteristics, while generalization identifies a superclass from common subclass features.
- Categories represent subclasses that can exist in multiple superclasses through a union.
- Constraints include disjointness, completeness, and whether subclasses are predicate-defined or user-defined.
This document discusses enhanced entity-relationship (EER) modeling concepts, including specialization, generalization, subclasses and superclasses. It provides an example of a library database with entities such as authors, books, subjects and libraries, and relationships such as wrote and carry. It explains how EER modeling allows representing more complex applications through concepts like subclasses that inherit attributes and relationships from superclasses.
RELATIONAL MODEL OF DATABASES AND OTHER CONCEPTS OF DATABASESEdwinJacob5
The document discusses different database models:
- The relational model was proposed by E.F. Codd and organizes data into tables with rows and columns. Popular relational DBMS include Oracle, SQL Server, and Access.
- The hierarchical model uses a tree structure where each item has a single predecessor and subordinates. It is natural for applications with parent-child relationships.
- The network model is a generalization of the hierarchical model, allowing many-to-many relationships through multiple parent segments connected through graphs.
- Other models discussed include the AI frame model which uses slots to flexibly arrange related information similarly to object-oriented representations.
Database systems can be summarized in 3 sentences:
A database system consists of a database, database management system (DBMS), and users. The database contains organized data, the DBMS manages access to the data and provides utilities for querying and updating it, and users interact with the system for data entry, retrieval, and administration. Over time, database models have evolved from hierarchical and network models to the prevalent relational model to better support data sharing and querying across systems.
Lecture Basic HTML tags. Beginning Web Site Design Stanford University Contin...Anwar Patel
A database management system (DBMS) allows users to create, maintain, and interact with databases by providing an interface to manage stored data and tools to manipulate and retrieve it efficiently. A relational database management system (RDBMS) organizes and stores data using a relational model with tables containing rows and columns. The relational model represents data entities as tables with attributes as columns and relationships as primary and foreign keys. The three main types of relationships are one-to-one, one-to-many, and many-to-many.
This document provides an introduction to object-oriented analysis and design (OOA/D). It discusses the key concepts of analysis, design, and the Unified Modeling Language (UML). It also provides an example of analyzing and designing a simple dice game to illustrate the process, including defining use cases, creating a domain model, interaction diagrams, and a design class diagram. The goal is to teach students how to apply OOA/D principles and the UML notation to create robust and maintainable software designs.
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1. 221
The Entity-Relationship Model
• After completing this chapter, you should be able to
explain the three phases of database design,
Why are multiple phases useful?
evaluate the significance of the Entity-Relationship Model
(ER model) for DB design,
enumerate the basic constructs of the ER model,
develop ER diagrams (schemas in the ER model) for a
given application,
translate ER models into equivalent (as far as possible)
relational models.
2. 222
The Entity-Relationship Model
Overview
1. Database Design Overview
2. Basic ER Constructs
3. Kinds of Relationships (Cardinalities)
4. Keys, Weak Entities
5. Translation into the Relational Model
3. 223
Database Design (1)
• Overall goal of DBMS usage: Efficiently develop programs to
support given real-world tasks.
• These programs need to store data persistently.
• To develop these programs, apply proven methods of software
engineering—specialized to support data-intensive programs.
Database Design
Database Design is the process of developing a
database schema for a given application.
DB design is a subtask of the overall software engineering
effort.
4. 224
Database Design (2)
• The specification of programs and data is intertwined:
The schema should contain the data needed by the
programs.
Programs are often easy to develop once the structure of
the data to be manipulated has been specified.
• Data, however, is an independent resource:
Typically, additional programs will be developed later based
on the collected data.
Also, ad-hoc queries will be posed against the DB.
5. 225
Database Design (3)
• During DB design, a formal model of the relevant aspects
of the real world (“mini world”, “domain of discourse”) must
be built.
Once the DB is up and running, questions will be posed against
the DB. Knowledge of these questions beforehand is important
input to the DB design process and helps to identify the
relevant parts of the real world.
• In some sense, the real world is the measure of correctness
for the DB schema: the possible DB states should correspond
to the states of the real world.
6. 226
Database Design (4)
• DB design is not easy for a variety of reasons:
Expertise: The designer must become an expert for the
application domain or needs to talk to such experts.
Depending on the domain, these experts might not be used
to give a complete and formal account of their field.
Flexibility: The real world typically permits exceptions and
corner cases. Does the DB schema need to reflect these?
Size: Database schemas may become huge (in terms of
number of relations, attributes, constraints).
• Due to this complexity, DB design is a multi-step process.
7. 227
Database Design (5)
Three Phases of DB Design
1 Conceptual Database Design. Produces the initial
model of the mini world in a conceptual data model
(e.g., in the ER model).
2 Logical Database Design. Transforms the conceptual
schema into the data model supported by the DBMS
(e.g., the relational model).
3 Physical Database Design. Design indexes, table
distribution, buffer size, etc., to maximize performance of
the final system (subject of “Datenbanken II ”).
8. 228
Database Design (6)
• Why multiple design phases?
Partition the problem, attack one sub-problem after the
other.
For example, during conceptual design there is no need to
worry about performance aspects or limitations of the
specific SQL dialect of the RDBMSs.
DBMS features do not influence the conceptual design and
only partially influence the logical design.
Thus, the conceptual design work is not invalidated, if a
different DBMS is used later on.
9. 229
Example (1)
• ER schema in graphical notation:
ER schema in graphical notation:
Instructor teaches Course
Name Phone No Title
This mini world talks about instructors and courses.
Instructors teach courses.
Instructors have a name and a phone number.
Courses are numbered and have titles.
10. 230
Example (2)
A possible state of this mini world
Instructor Course
Nogg3 42232
g
ggggg
lll • WWWWWWW
ll WW+
Grust kWWWW lll
WWWW lllll
Name Title XML
ggg • RRRR
sggggg RRR
RRR
7111 Phone RRR Nogg3 20727
g
gWggg
• WgWWWW
WWW+
Title DB1
11. 231
The ER Model (1)
• The Entity-Relationship Model is often referred to as a
semantic data model, because it more closely resembles real
world scenarios than, e.g., the relational model.
In the ER model, we model the concept of “Instructors.”
In the relational model we deal with names and phone
numbers.
In the ER model, there is a distinction between entities
(objects) and relationships between such entities.
In the relational model, both concepts are represented by
relations.
12. 232
The ER Model (2)
• Proposed by Peter Chen (1976), today at Louisiana State
University (http://bit.csc.lsu.edu/∼chen/chen.html).
• The ER model comes with a graphical notation which helps
to establish quick overviews of database application schemas.
Such ER diagrams are also a great way to communicate
schemas to non-expert/future DB users.
• There are no “ER Model DBMS”.
Instead, we will describe a translation of ER model concepts
into the relational model.
13. 233
The Entity-Relationship Model
Overview
1. Database Design Overview
2. Basic ER Constructs
3. Kinds of Relationships (Cardinalities)
4. Keys, Weak Entities
5. Translation into the Relational Model
14. 234
Basic ER Model Concepts (1)
• Entities:
An object in the mini world about which information is to
be stored. Examples: persons, books, courses.
Note: entities do not have to correspond to objects of
physical existence. Entities may also represent conceptual
objects like, e.g., vacations.
The mini world that has to be modelled can contain only a
finite number of objects.
It must be possible to distinguish entities from each other,
i.e., objects must have some identity.
Examples: entity book identified by ISBN number, entity
vacations identified by travel agency booking number.
15. 235
Basic ER Model Concepts (2)
• Attribute:
A property or feature of an entity (or relationship, see
below).
Example: the title of this course entity is “Foundations of
Databases.”
The value of an attribute is an element of a data type like
string, integer, date.
These values have a printable representation (which
entities have not).
16. 236
Basic ER Model Concepts (3)
• Relationship:
A relation—not in the strict relational model
sense—between pairs of entities (a binary relationship).
Example: Grust (an entity) teaches (a relationship) the
course “Foundations of Databases” (an entity).
17. 237
ER Diagrams (1)
• Entity E:
E
• Attribute A of Entity Type E:
E A
• Relationship R between Entity Types E1 and E2 :
E1 R E2
18. 238
ER Diagrams (2)
• Relationships may also exist entities of the same type
(“recursive relationship”):
is precondition for
Course Precondition
requires knowledge of
• In this case, role names have to be attached to the
connecting edges.
In the ER model, role names may be attached to any kind of
relationship for documentation purposes.
19. 239
ER Diagrams (3)
• Relationships may have attributes, too:
Student solved Exercise
points
This models the fact that a number of points is stored for
every pair of a student X and an exercise Y such that X
submitted a solution for Y .
20. 240
Graphical Syntax
1 An ER diagram contains
• boxes, diamonds, ovals, plus interconnecting lines.
2 Boxes, diamonds, and ovals are each labelled by a string.
• Box labels are unique in the entire diagram.
• Oval labels are unique for a single box or diamond.
• Diamond labels are unique for a pair of connected boxes.
3 Interconnecting lines are only allowed between
• box—diamond, box—oval, diamond—oval.
4 A diamond has exactly two connecting lines to boxes. There
may be any number of connections to ovals.
5 An oval has exactly one connecting line.
21. 241
ER Example
Modelling a Mini World: Define an ER Diagram
• Information about researchers in the database field is to be
stored.
• For each researcher, his/her last name, first name, e-mail ad-
dress, and homepage URI are relevant.
• Researchers are affiliated with universities and assume a cer-
tain position (e.g., professor, lecturer).
• Relevant university information are the name, homepage URI,
and country.
• Researchers publish articles (of a given title) in journals.
22. 242
The Entity-Relationship Model
Overview
1. Database Design Overview
2. Basic ER Constructs
3. Kinds of Relationships (Cardinalities)
4. Keys, Weak Entities
5. Translation into the Relational Model
23. 243
Cardinalities (1)
• General ER relationship:
E1 R E2
aa
aaaaaaaaa •
• VVVVV aaa
a
VVVVV
• VVVVV •
V
aaaaaaaaa •
• aaaaaafffffffff
f
ffff
• ff
•
•
•
•
24. 244
Cardinalities (2)
• In general, there is no restriction on how often an entity
participates in an relationship R.
An entity can be connected to one entity of the other type,
to more than one, or it can have no R-partner at all.
• However, specific application semantics dictate to how many
E2 entities an E1 entity can be related:
Man is married to Woman
25. 245
Cardinalities (3)
• The ER model introduces the (min, max) notation to specify
an interval of possible participations in an relationship:
E1 (m1 , n1 ) R (m2 , n2 ) E2
An entity of type E1 may be related to at least m1 and at
most n1 entities of type E2 .
Likewise, m2 is the minimum number and n2 is the maximum
number of E1 entities to which an E2 entity is related
26. 246
Cardinalities (4)
• Extensions:
“∗” may be used as maximum if there is no limit.
(0, ∗) means no restriction at all (general relationship).
27. 247
Cardinalities (5)
Marriage
Man (0,1) is married to (0,1) Woman
“A man can be married to at most one woman and vice versa.”
Airport Locations
Airport (1,1) lies in (0,*) Country
“An airport lies in exactly one country. A country may have
arbitrarily many airports (and maybe none at all).”
28. 248
Cardinalities (6)
Derive cardinalities from verbal specifications
“Besides normal customers, the database may contain
customers who have not yet ordered anything.”
Order ( , ) from ( , ) Customer
Derive cardinalities from verbal specifications
“An order can contain several products.”
Order ( , ) for ( , ) Product
29. 249
Selecting Cardinalities
• Sometimes a sketch of a valid database state may help in
selecting the right cardinalities, e.g., for the state sketched on
slide 243, a viable cardinality for E1 —R may be (0, 3).
• Application knowledge might lead to weaker restrictions, in
this example (0, 5) or (0, ∗).
A cardinality (a, b) is weaker than (c, d) if a c and d b.
• In real applications, the cardinalities (0, 1), (1, 1), and (0, ∗)
are the most common and especially easy to enforce in the
relational model.
30. 250
Common Cases (1)
• Normally, the minimum cardinality will be 0 or 1, and the
maximum cardinality will be 1 or ∗.
Thus, only the (0, 1), (1, 1), (0, ∗), (1, ∗) cardinalities are
common in practice.
• To understand a relationship, one must know the cardinality
specifications on both sides.
• The maximum cardinalities on each side are used to
distinguish between many-to-many, one-to-many /
many-to-one, and one-to-one relationships.
31. 251
Common Cases (2)
• Many-to-many relationships:
Both maximum cardinalities are ∗ (the minimum
cardinalities are 0 or 1):
Many-to-many relationship
Student (0,*) takes (0,*) Course
This is the most general/least restrictive case of a
relationship.
When translated into the relational model, the
representation of many-to-many relationships requires an
extra table.
32. 252
Common Cases (3)
• One-to-many relationships:
Maximum cardinality 1 on the “many” side and ∗ on the
“one” side:
One-to-many relationship
Instructor (0,*) teaches (1,1) Course
“One instructor teaches many courses, but each course
is run by exactly one instructor.”
One-to-many relationships do not require an extra table in
an equivalent representation in the relational model.
33. 253
Common Cases (4)
• One-to-one relationships:
Maximum cardinality 1 on both sides:
One-to-one relationship
Employee (0,1) is head of (1,1) Department
“Each department has exactly one department head,
some employees are the head of one department.”
• Note how mandatory or optional participation in an
relationship determines the minimum cardinalities.
34. 254
Cardinalities: Alternative Notations (1)
• Widespread variants of notations for cardinalities:
Leave particpiation unspecified:
Cardinalities are either many-to-many (N:M),
one-to-many (1:N), or one-to-one (1:1).
One-to-many relationship
Instructor 1 teaches N Course
35. 255
Cardinalities: Alternative Notations (2)
• Sometimes found in software supporting visual ER diagram
development (e.g., in Oracle DesignerTM ):
One-to-many relationship
'& %$ teaches r '& Course %$
! Instructor "#_ _ _ _ _ _ L ! "#
r
L
taught by
The “crow foot” indicates the “many” side.
Dashed lines indicate optional participiation.
Relationship roles are given (for both sides).
36. 256
The Entity-Relationship Model
Overview
1. Database Design Overview
2. Basic ER Constructs
3. Kinds of Relationships (Cardinalities)
4. Keys, Weak Entities
5. Translation into the Relational Model
37. 257
Keys (1)
ER Key
A key K of an entity type E a is an attribute of E which
uniquely identifies the entities of this type. No two
different entities share the same value for the key
attribute. Composite keys are allowed.
K
E A1
A2
a Only entity types can have key attributes.
38. 258
Keys (2)
• The translation of ER schemas into relational schemas
requires the declaration of ER keys.
• If there is no natural key, add artificial identifiers (e.g.,
integers, remember attributes EMPNO, DEPTNO from Chapter 1)
which then represent the entities.
39. 259
Weak Entities (1)
• In many schemas, some entities describe a kind of detail that
cannot exist without a master (or owner) entity.
In such a case,
1 there is a relationship with cardinality (1, 1) on the
detail entity side, and in addition
2 the key of the master is inherited and becomes part of
the key of the detail entity.
Inv No Inv No
Invoice (1, ∗) has (1, 1) Position
Date Pos
40. 260
Weak Entities (2)
• Without a specific ER construct for this case, we would
require the following additional constraint:
If two entities are in “has” relationship,
then their attribute “Inv No” are required to have identical
values.
For example, invoice #12 cannot have position 2 in invoice
#42 as detail.
• Such constraints occur if an entity does not have a key by
itself, but it is only unique in the context of some other
(master) entity.
41. 261
Weak Entities (3)
• Note: In such cases, keys are always composite.
Examples:
A classroom is identified by a building and a room number.
A section in a book is identified by a chapter and a section
title.
A web page URI is composed of a web server DNS address
and a path on that server.
• There is also an existence dependency.
If the building is pulled down, the classrooms automatically
disappear. If the web server is shut down, all URIs on that
server cease to function.
42. 262
Weak Entities (4)
• In the ER model, such scenarios are modelled via weak
entities3 .
• In ER diagrams, weak entities and their identifying
relationships are indicated by double lines:
Inv No
Invoice (1, ∗) has (1, 1) Position Pos
Date
• For the weak entity, the inherited part of the key is not
shown.
3 Non-weak entities are also called strong entities.
43. 263
Weak Entities (5)
Modelling with weak entities
Model a set of online quizzes (multiple choice tests).
• Each quiz is identified by a title, each question within a
quiz is numbered, and each possible answer to a given
question is referenced by a letter.
For each question and answer, the associated text is
stored. Answers are classified into correct and incorrect
ones.
• What is the complete key for each of the occurring
entity types?
44. 264
The Entity-Relationship Model
Overview
1. Database Design Overview
2. Basic ER Constructs
3. Kinds of Relationships (Cardinalities)
4. Keys, Weak Entities
5. Translation into the Relational Model
45. 265
ER Diagram Example
CustNo
Customer Name
(0, ∗) Phone
places
(1, 1) Description
Order (0, ∗) for (0, ∗) Product
OrdNo Date Quantity ProdNo Price
46. 266
Step 1: Entities (1)
• Transforming an ER entity E:
1 Create a table for each entity.
The table name is E (conventionally: E + ’s’).
2 The columns of this table are the attributes of the
entity type.
3 The primary key of the table is the primary key of the
entity type.
If E’s key is composite, so will be the relational key. If E
has no key, add an artifical key to the table.
47. 267
Step 1: Entities (2)
Customers Orders
CustNo Name Phone OrdNo Date
10 Jones 624-9404 200 2/15/04
11 Smith 201 2/16/04
Products
ProdNo Description Price
1 Apple 0.50
2 Kiwi 0.25
3 Orange 0.60
48. 268
Step 1B: Weak Entities
Invoice (1, ∗) has Position
Inv No Date Pos
• When a weak entity is translated, the key attributes of the
owner entity are added as a key and foreign key:
Position (Pos, Inv No → Invoice, ...)
This automatically implements the relationship.
It makes sense to specify DELETE CASCADES for the foreign
key: if an invoice is deleted, all its positions will be removed
from the DB state, too.
49. 269
Step 2: One-To-Many Relationships (1)
• Transforming a relationship R:
1 If R has maximum cardinality 1 on one side, R is
one-to-many4 .
Example: Customer–(0, ∗)–places–(1, 1)–Order, “one
customer places many orders.”
2 In this case, add the key of the “one” side as a column
to the “many” table to implement R.
3 This column will be a foreign key referencing a row in
the table representing the related entity.
4 If R has maximum cardinality 1 on both sides, it is actually one-to-one,
see below.
50. 270
Step 2: One-To-Many Relationships (2)
Orders (OrdNo, Date, CustNo → Customers)
Orders
OrdNo Date CustNo
200 2/15/04 11
201 2/16/04 11
Customers
CustNo Name Phone
10 Jones 624-9404
11 Smith
• Convention: use relationship and role to name foreign key
column:
Orders (OrdNo, Date, placed by → Customers)
51. 271
Step 2: One-To-Many Relationships (3)
• Transforming a one-to-many relationship R:
4 If the minimum cardinality is 1 on the “many” side (see
example), null values are not allowed in the foreign key
column (column placed by in example).
If the minimum cardinality is 0, null values are allowed
in the foreign key column.
The foreign key is null for those entities that do not
participate in R at all.
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Step 2: Relationship Attributes
• To transform one-to-many relationship attribute(s), e.g.
Student (0, ∗) borrowed (0, 1) Book
Stud ID Date ISBN
store the relationship attribute(s) together with the
reference to the related entity, e.g.
Books (ISBN, ..., borrowed by → Students, Date)
53. 273
Step 2: One-To-Many Relationships: A Variant
• One-to-many relationships R with cardinality (0,1) can be
translated into a table of their own:
borrowed by (ISBN→Books, Stud ID→Students, Date)
• The extra table holds the key values of the related entities
plus the relationship attributes.
• The key attributes of the side with the (0,1) cardinality
become the key of this relation.
“Each book can be borrowed only once at the same time.”
This does not model R correctly if the cardinality is (1,1)
Why?
54. 274
Step 3: Many-To-Many Relationships (1)
• Transforming a many-to-many relationship R:
1 If R has maximum cardinality ∗ on both sides, R is
many-to-many.
Example: Order–(1, ∗)–for–(0, ∗)–Product, “an order
contains many products, a product may be part of many
orders.”
2 R becomes its own table.
3 The columns of this table are the keys of both
participating entity types.
4 These columns act as foreign keys referencing the entities
and, at the same time, together form a composite key
for the extra table.
55. 275
Step 3: Many-To-Many Relationships (2)
• Transforming a many-to-many-relationship R:
5 Relationship attributes are added as columns to the table
representing R.
for (OrdNo→Orders, ProdNo→Products, Quantity)
Composite key?
Is it really necessary that both entity keys (here: OrdNo,
ProdNo) form a composite key for the relationship table?
57. 277
Step 3: Many-To-Many Relationships (4)
• Transforming a many-to-many relationship R:
Note: Minimum cardinalties other than 0 for R cannot be
enforced by the relational model per se, i.e., in terms of key
constraints.
Order–(0, ∗)–for–(1, ∗)–Product ⇔ “Every product occurs in
at least one order.”
If this is important to guarantee database consistency (valid
DB state), this constraint needs to be checked by the
application program or a general RDBMS constraint
mechanism.
58. 278
Step 4: One-To-One Relationships (1)
• Transforming a one-to-one relationship R:
Department (1, 1) led by (0, 1) Employee
DName ID
1 If R has maximum cardinality 1 on both sides, R is
one-to-one.
2 We can essentially transform as if R were one-to-many,
but additional key constraints are generated.
59. 279
Step 4: One-To-One Relationships (2)
• To which entity table shall we add the led by attribute to
represent the relationship?
Department (1, 1) led by (0, 1) Employee
DName ID
Since we have Department–(1, 1)–led by (“every
department is led by exactly one employee”), it makes sense
to host the relationship in the Department table:
Department (DName, ..., led by → Employee)
We may declare the foreign key led by as NOT NULL. (This
is not possible if led by is hosted in the Employee table.)
60. 280
Step 4: One-To-One Relationships (3)
Department (1, 1) led by (0, 1) Employee
DName ID
Department (DName, ..., led by → Employee)
• Note: led by now also is a key for the Department table.
led by is a key for table Department
Why is this the case in this example?
• This key constraint enforces the maximum cardinality of 1 (on
the Employee side).
61. 281
Step 4: One-To-One Relationships (4)
Man (0, 1) married (0, 1) Woman
MName Born WName Born
• Two variants:
1 Any of the two (not both!) entity tables may host the
married foreign key (null values allowed).
2 Translate the relationship into a table of its own:
married (MName → Man, WName → Woman)
A one-to-one relationship in an extra table
What would be the correct key(s) for table married?
62. 282
Step 4: One-To-One Relationships (5)
Customer (1, 1) has (1, 1) Card
SSN Name CardNo CreditLimit
• In order to enforce the minimum cardinality 1 on both
sides, the entity tables need to be merged:
CustomerCard (SSN, Name, CardNo, CreditLimit)
No null values are allowed.
Both, SSN and CardNo, are keys of this table. One is
selected as primary key, the other is an secondary key.
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Limitations (1)
• The following ER relationship cardinalities can be faithfully
represented in the relational model:
E1 (1, 1) R (0, ∗) E2 E1 (1, 1) R (0, 1) E2
E1 (0, 1) R (0, ∗) E2 E1 (0, 1) R (0, 1) E2
E1 (0, ∗) R (0, ∗) E2 E1 (1, 1) R (1, 1) E2
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Limitations (2)
• For all other cardinalities, the constraint mechanisms of the
relational model will not suffice.
Order (1, ∗) for (0, ∗) Product
No ID
“Every purchase order includes at least one product item.”
Relational (foreign) key constraints cannot enforce the
minimum cardinality 1.
⇒ Apply the translation method for (0, ∗) cardinalities and
enforce the constraint in the application (or via an RDBMS
trigger whenever a tuple in table Order is inserted).